Data Preparation

Import Dataset

Data Preprocess

Defining Preprocess Recipe

#> [1] 306  44
#> [1] 306   2

Model Fitting

Defining Model Architecture

#> ___________________________________________________________________________
#> Layer (type)                     Output Shape                  Param #     
#> ===========================================================================
#> input (InputLayer)               (None, 44)                    0           
#> ___________________________________________________________________________
#> dense_1 (Dense)                  (None, 32)                    1440        
#> ___________________________________________________________________________
#> dense_1_act (LeakyReLU)          (None, 32)                    0           
#> ___________________________________________________________________________
#> dense_1_bn (BatchNormalizationV1 (None, 32)                    128         
#> ___________________________________________________________________________
#> dense_1_dp (Dropout)             (None, 32)                    0           
#> ___________________________________________________________________________
#> output (Dense)                   (None, 2)                     66          
#> ___________________________________________________________________________
#> output_bn (BatchNormalizationV1) (None, 2)                     8           
#> ___________________________________________________________________________
#> output_act (Activation)          (None, 2)                     0           
#> ===========================================================================
#> Total params: 1,642
#> Trainable params: 1,574
#> Non-trainable params: 68
#> ___________________________________________________________________________

Model Evaluation

Predict on Test Dataset

Confusion Matrix

ROC Curve

Precision-Recall Curve